49 resultados para Input-Output Modelling


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This paper estimates the elasticity of labor productivity with respect to employment density, a widely used measure of the agglomeration effect, in the Yangtze River Delta, China. A spatial Durbin model is presented that makes explicit the influences of spatial dependence and endogeneity bias in a very simple way. Results of Bayesian estimation using the data of the year 2009 indicate that the productivity is influenced by factors correlated with density rather than density itself and that spatial spillovers of these factors of agglomeration play a significant role. They are consistent with the findings of Ke (2010) and Artis, et al. (2011) that suggest the importance of taking into account spatial dependence and hitherto omitted variables.

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This paper presents a simulation of the reduction of several components in trade cost for Asia and examines its impact on the economy. Our simulation model based on the new economic geography embraces seven sectors, including manufacturing and non-manufacturing sectors, and 1,715 regions in 18 countries/economies in Asia, in addition to the two economies of the US and the European Union. The geographical course of transactions among regions is modeled as determined based on firms’ modal choice. The model also includes estimates of some border cost measures such as tariff rates, non-tariff barriers, other border clearance costs, transshipment costs and so on. Our simulation analysis for Asia includes several scenarios involving the improvement/development of routes and the reduction of the above-mentioned border cost. We have shown that the contribution of physical and non-physical infrastructure improvements conducted together is larger than the sum of the contribution by each when conducted independently.

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This paper estimates the impact of industrial agglomeration on firm-level productivity in Chinese manufacturing sectors. To account for spatial autocorrelation across regions, we formulate a hierarchical spatial model at the firm level and develop a Bayesian estimation algorithm. A Bayesian instrumental-variables approach is used to address endogeneity bias of agglomeration. Robust to these potential biases, we find that agglomeration of the same industry (i.e. localization) has a productivity-boosting effect, but agglomeration of urban population (i.e. urbanization) has no such effects. Additionally, the localization effects increase with educational levels of employees and the share of intermediate inputs in gross output. These results may suggest that agglomeration externalities occur through knowledge spillovers and input sharing among firms producing similar manufactures.

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Global value chains are supported not only directly by domestic regions that export goods and services to the world market, but also indirectly by other domestic regions that provide parts, components, and intermediate services to final exporting regions. In order to better understand the nature of a country’s position and degree of participation in global value chains, we need to more fully examine the role of individual domestic regions. Understanding the domestic components of global supply chains is especially important for large developing countries like China and India, where there may be large variations in economic scale and development between domestic regions. This paper proposes a new framework for measuring domestic linkages to global value chains. This framework measures domestic linkages by endogenously embedding a country’s domestic interregional input-output (IO) table in an international IO model. Using this framework, we can more clearly describe how global production is fragmented and extended through linkages across a country’s domestic regions. This framework will also enable us to estimate how value added is created and distributed in both domestic and international segments of global value chains. For examining the validity and usefulness of this new approach, some numerical results are presented and discussed based on the 2007 Chinese interregional IO table, China customs statistics at the provincial level, and World Input-Output Tables (WIOTs).

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This paper presents a framework for an SCGE model that is compatible with the Armington assumption and explicitly considers transport activities. In the model, the trade coefficient takes the form of a potential function,and the equilibrium market price becomes similar to the price index of varietal goods in the context of new economic geography (NEG). The features of the model are investigated by using the minimal setting, which comprises two non-transport sectors and three regions. Because transport costs are given exogenously to facilitate study of their impacts, commodity prices are also determined relative to them. The model can be described as a system of homogeneous equations, where an output in one region can arbitrarily be determined similarly as a price in the Walrasian equilibrium. The model closure is sensitive to formulation consistency so that homogeneity of the system would be lost by use of an alternative form of trade coefficients.

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This study focuses on the technological intensity of China's exports. It first introduces the method of decomposing gross exports by using the Asian international input–output tables. The empirical results indicate that the technological intensity of Chinese exports has been significantly overestimated due to its high dependency on import content, especially in high-technology exports, an area highly dominated by the electronic and electrical equipment sector. Furthermore, a significant portion of value added embodied in China's high-technology exports comes from services and high-technology manufacturers in neighboring economies, such as Japan, South Korea, and Taiwan.

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This paper integrates two lines of research into a unified conceptual framework: trade in global value chains and embodied emissions. This allows both value added and emissions to be systematically traced at the country, sector, and bilateral levels through various production network routes. By combining value-added and emissions accounting in a consistent way, the potential environmental cost (amount of emissions per unit of value added) along global value chains can be estimated. Using this unified accounting method, we trace CO2 emissions in the global production and trade network among 41 economies in 35 sectors from 1995 to 2009, basing our calculations on the World Input–Output Database, and show how they help us to better understand the impact of cross-country production sharing on the environment.

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Structural transformations are an indispensable element of sustained economic growth. Within the context of East Asia, this study focuses on industrial deepening, which refers to the formation of local linkages and the creation of a robust local supplier base. To investigate the progress of industrial deepening, this study introduces two kinds of domestic procurement measures in addition to the previously developed local content measures. Specifically, two kinds of vertical specialization measures are used to demonstrate the degree to which respective East Asian economies are specialized within their vertical production networks. The results clearly show that the advancement of production networks is likely to reduce domestic procurement ratios, even if local supplier bases are strengthened in the respective countries. Moreover, the trend of domestic procurement ratios differs depending on the characteristics of particular industries and the industrial policies adopted by individual countries.

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This study adopts the perspective of demand spillovers to provide new insights regarding Chinese domestic-regions' production position in global value chains and their associated CO2 emissions. To this end, we constructed a new type of World Input-Output Database in which China's domestic interregional input-output table for 2007 is endogenously embedded. Then, the pattern of China's regional demand spillovers across both domestic regions and countries are revealed by employing this new database. These results were further connected to endowments theory, which help to make sense of the empirical results. It is found that China's regions locate relatively upstream in GVCs, and had CO2 emissions in net exports, which were entirely predicted by the environmental extended HOV model. Our study points to micro policy instruments to combat climate change, for example, the tax reform for energy inputs that helps to change the production pattern thus has impact on trade pattern and so forth.

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The concept and logic of the "smile curve" in the context of global value chains has been widely used and discussed at the individual firm level, but rarely identified and investigated at the country and industry levels by using real data. This paper proposes an idea, based on an inter-country input-output model, to consistently measure both the strength and length of linkages between producers and consumers along global value chains. This idea allows for better identification and mapping of smile curves for countries and industries according to their positions and degrees of participation in a given conceptual value chain. Using the 1995-2011 World Input-Output Tables, several conceptual value chains are investigated, including exports of electrical and optical equipment from China and Mexico and exports of automobiles from Japan and Germany. The identified smile curves provide a very intuitive and visual image, which can significantly improve our understanding of the roles played by different countries and industries in global value chains. Further, the smile curves help identify the benefits gained by these countries and industries through their participation in global trade.

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We exploit the recent release of the 2005 Asian Input-Output Matrix to dress a picture of the geographic fragmentation of value added in Factory Asia from 1990 to 2005. We document 3 stylized facts. The first is that the average share of foreign value added embedded in production rose by about 7 percentage points between 1990 and 2005, from 9% to 16%. The second is that, contrary to popular belief, China's production embeds a smaller share of foreign value added than other Factory Asia countries'. Between 1990 and 2005 among Factory Asia countries China grew most after Japan as a source of value added to other countries' production. Third, country-industries at the upstream and downstream extremities of the supply chain embed a smaller share of foreign value added than those with intermediate levels of upstreamness.

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Koopman et al. (2014) developed a method to consistently decompose gross exports in value-added terms that accommodate infinite repercussions of international and inter-sector transactions. This provides a better understanding of trade in value added in global value chains than does the conventional gross exports method, which is affected by double-counting problems. However, the new framework is based on monetary input--output (IO) tables and cannot distinguish prices from quantities; thus, it is unable to consider financial adjustments through the exchange market. In this paper, we propose a framework based on a physical IO system, characterized by its linear programming equivalent that can clarify the various complexities relevant to the existing indicators and is proved to be consistent with Koopman's results when the physical decompositions are evaluated in monetary terms. While international monetary tables are typically described in current U.S. dollars, the physical framework can elucidate the impact of price adjustments through the exchange market. An iterative procedure to calculate the exchange rates is proposed, and we also show that the physical framework is also convenient for considering indicators associated with greenhouse gas (GHG) emissions.

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This paper proposes an alternative input-output based spatial-structural decomposition analysis to elucidate the role of domestic-regional heterogeneity and interregional spillover effects in determining China's regional CO2 emission growth. Our empirical results based on the 2007 and 2010 Chinese interregional input-output tables show that the changes in most regions' final demand scale, final expenditure structure and export scale give positive spatial spillover effects on other regions' CO2 emission growth, the changes in most regions' consumption and export preference help the reduction of other regions' CO2 emissions, the changes in production technology, and investment preference may give positive or negative impacts on other region's CO2 emission growth through domestic supply chains. For some regions, the aggregate spillover effect from other regions may be larger than the intra-regional effect in determining regional emission growth. All these facts can significantly help better and deeper understanding on the driving forces of China's regional CO2 emission growth, thus can enrich the policy implication concerning a narrow definition of "carbon leakage" through domestic-interregional trade, and relevant political consensus about the responsibility sharing between developed and developing regions inside China.

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Using an augmented Chinese input–output table in which information about firm ownership and type of traded goods are explicitly reported, we show that ignoring firm heterogeneity causes embodied CO2 emissions in Chinese exports to be overestimated by 20% at the national level, with huge differences at the sector level, for 2007. This is because different types of firm that are allocated to the same sector of the conventional Chinese input–output table vary greatly in terms of market share, production technology and carbon intensity. This overestimation of export-related carbon emissions would be even higher if it were not for the fact that 80% of CO2 emissions embodied in exports of foreign-owned firms are, in fact, emitted by Chinese-owned firms upstream of the supply chain. The main reason is that the largest CO2 emitter, the electricity sector located upstream in Chinese domestic supply chains, is strongly dominated by Chinese-owned firms with very high carbon intensity.